Xü Lin

89 papers receiving 1.4k citations

Peers

Xü Lin
Comparison fields: 5 of 137
  • Modeling and Simulation 57
  • Health 59
  • Otorhinolaryngology 27
  • Cancer Research 83
  • Oncology 144
Replace Marianna de Camargo Cancela with:
Marianna de Camargo Cancela Brazil
Kevin Henry United States
Megan Scudellari United States
Denny John India
Erin N. Kobetz United States
Henry Liu United States
Yang Meng United Kingdom
Prashanth Nuggehalli Srinivas India
Yaoguang Zhang China
Xü Lin relative to Marianna de Camargo Cancela Brazil Marianna de Camargo Cancela's profile →
Citations per field
00.5×1.5×1.9×
Marianna de Camargo Cancela · 1×
Citations per year

Countries citing papers authored by Xü Lin

Since Specialization
Citations

This map shows the geographic impact of Xü Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xü Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xü Lin more than expected).

Fields of papers citing papers by Xü Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xü Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xü Lin. The network helps show where Xü Lin may publish in the future.

Co-authors

The 25 scholars most cited alongside Xü Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xü Lin Line = papers co-authored together Xü Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 96 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202098
2
Influence of MDR1 gene codon 3435 polymorphisms on outcome of platinum-based chemotherapy for advanced non small cell lung cancer.
201156
3 202356
4 201354
5 201252
6 201650
7 202345
8 202045
9 202344
10 202040
11 202139
12 201536
13 201236
14 201335
15 201334
16 202034
17 202032
18
Lack of any relationship between chemotherapy toxicity in non-small cell lung cancer cases and polymorphisms in XRCC1 codon 399 or XPD codon 751.
201125
19 201925
20 202323

About Xü Lin

Xü Lin is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Public Health, Environmental and Occupational Health, Surgery and Epidemiology, having authored 96 papers that have together received 1.4k indexed citations. Recurring topics across this work include Legal, Health, Environmental and COVID-19 Challenges (7 papers), Zoonotic diseases and public health (4 papers), COVID-19 epidemiological studies (4 papers), Environmental and Biological Research in Conflict Zones (4 papers), Diverse Scientific Research in Ukraine (4 papers), Plant-Microbe Interactions and Immunity (3 papers), Epigenetics and DNA Methylation (3 papers) and Vaccine Coverage and Hesitancy (3 papers). The work is most often cited by research in Modeling and Simulation (57 citations), Health (59 citations), Otorhinolaryngology (27 citations), Cancer Research (83 citations) and Oncology (144 citations). Xü Lin has collaborated with scholars based in China, United Kingdom and Philippines. Frequent co-authors include Don Eliseo Lucero‐Prisno, Yusuff Adebayo Adebisi, Xin‐En Huang, Attaullah Ahmadi, Mohammad Yasir Essar, Yan-Yan Lu, Martin C. S. Wong, Zhi‐Jie Zheng, Wanghong Xu and Sze Chai Chan. Their work appears in journals such as Journal of Global Health, Global Health Research and Policy, Materials & Design, Frontiers in Bioengineering and Biotechnology and Annals of Medicine.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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